• Infrared and Laser Engineering
  • Vol. 50, Issue 5, 20200364 (2021)
Yuanhong Mao, Zhong Ma*, and Zhanzhuang He
Author Affiliations
  • Xi’an Microelectronics Technology Institute, Xi’an 710065, China
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    DOI: 10.3788/IRLA20200364 Cite this Article
    Yuanhong Mao, Zhong Ma, Zhanzhuang He. Infrared-visible image patches matching via convolutional neural networks[J]. Infrared and Laser Engineering, 2021, 50(5): 20200364 Copy Citation Text show less
    References

    [1] Weiping Yang, Zhenkang Shen. Matching technique and its application in aided inertial navigation. Infrared and Laser Engineering, 36, 15-17(2007).

    [2] Hongguang Li, Wenrui Ding, Xianbin Cao, et al. Image registration and fusion of visible and infrared integrated camera for medium-altitude unmanned aerial vehicle remote sensing. Remote Sensing, 9, 441(2017).

    [3] Ning Wang, Ming Zhou, Qinglei Du. A method for infrared visible image fusion and target recognition. Journal of Air Force Early Warning Academy, 33, 328-332(2019).

    [4] Yuanhong Mao, Zhanzhuang He, Zhong Ma. Infrared target classification with reconstruction transfer learning. Journal of University of Electronic Science and Technology of China, 49, 609-614(2020).

    [5] D G Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60, 91-110(2004).

    [6] Bay H, Tuytelaars T, Gool L V. SURF: Speeded up robust features[C]European Conference on Computer Vision, 2006, 3951: 404–417.

    [7] Rublee E, Rabaud V, Konolige K, et al. B: An efficient alternative to SIFT SURF[C]International Conference on Computer Vision, 2011: 25642571.

    [8] A A Sima, S J Buckley. Optimizing SIFT for matching of short wave infrared and visible wavelength images. Remote Sensing, 5, 2037-2056(2013).

    [9] D M Li, J L Zhang. A improved infrared and visible images matching based on SURF. Applied Mechanics and Materials, 2418, 1637-1640(2013).

    [10] Zhiguo Chao, Bo Wu. Approach on scene matching based on histograms of oriented gradients. Infrared and Laser Engineering, 41, 513-516(2012).

    [11] Zhiguo Cao, Ruicheng Yan, Jie Song. Approach on fuzzy shape context matching between infrared images and visible images. Infrared and Laser Engineering, 37, 1095-1100(2008).

    [12] Anbo Jiao, Liyun Shao, Chenxi Li, et al. Automatic target recognition algorithm based on affine invariant feature of line grouping. Infrared and Laser Engineering, 48, S226003(2019).

    [13] Han X, Leung T, Jia Y, et al. Match: Unifying feature metric learning f patchbased matching[C]IEEE Conference on Computer Vision Pattern Recognition (CVPR), 2015: 32793286.

    [14] Zaguyko S, Komodakis N. Learning to compare image patches via convolutional neural wks[C]IEEE Conference on Computer Vision Pattern Recognition (CVPR), 2015: 43534361.

    [15] M S Hanif. Patch match networks: Improved two-channel and Siamese networks for image patch matching. Pattern Recognition Letters, 120, 54-61(2019).

    [16] Simonyan K, Zisserman A. Very deep convolutional wks f largescale image recognition[C]ICLR 2015: International Conference on Learning Representations, 2015.

    [17] Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[C]IEEE Conference on Computer Vision Pattern Recognition (CVPR), 2015: 19.

    [18] Hadsell R, Chopra S, LeCun Y. Dimensionality reduction by learning an invariant mapping[C]IEEE Computer Society Conference on Computer Vision Pattern Recognition (CVPR’06), 2006, 2: 17351742.

    [19] Schroff F, Kalenichenko D, Philbin J. Face: A unified embedding f face recognition clustering[C]IEEE Conference on Computer Vision Pattern Recognition (CVPR), 2015: 815823.

    [20] Glot X, Bengio Y. Understing the difficulty of training deep feedfward neural wks[C]Proceedings of the Thirteenth International Conference on Artificial Intelligence Statistics, 2010: 249256.

    [21] der Maaten L Van, G Hinton. Visualizing data using t-SNE. Journal of Machine Learning Research, 9, 2579-2605(2008).

    Yuanhong Mao, Zhong Ma, Zhanzhuang He. Infrared-visible image patches matching via convolutional neural networks[J]. Infrared and Laser Engineering, 2021, 50(5): 20200364
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